research-article

Event-based social networks: linking the online and offline social worlds

Authors:

Wang-Chien Lee,

John McPherson,

Jiawei HanAuthors Info & Claims

KDD '12: Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining

Pages 1032 - 1040

https://doi.org/10.1145/2339530.2339693

Published: 12 August 2012 Publication History

Abstract

Newly emerged event-based online social services, such as Meetup and Plancast, have experienced increased popularity and rapid growth. From these services, we observed a new type of social network - event-based social network (EBSN). An EBSN does not only contain online social interactions as in other conventional online social networks, but also includes valuable offline social interactions captured in offline activities. By analyzing real data collected from Meetup, we investigated EBSN properties and discovered many unique and interesting characteristics, such as heavy-tailed degree distributions and strong locality of social interactions.

We subsequently studied the heterogeneous nature (co-existence of both online and offline social interactions) of EBSNs on two challenging problems: community detection and information flow. We found that communities detected in EBSNs are more cohesive than those in other types of social networks (e.g. location-based social networks). In the context of information flow, we studied the event recommendation problem. By experimenting various information diffusion patterns, we found that a community-based diffusion model that takes into account of both online and offline interactions provides the best prediction power.

This paper is the first research to study EBSNs at scale and paves the way for future studies on this new type of social network. A sample dataset of this study can be downloaded from http://www.largenetwork.org/ebsn.

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https://dl.acm.org/doi/10.1016/j.ipm.2024.103966
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Zhu ZYuan GZhou TCao J(2024)Community Detection for Heterogeneous Multiple Social NetworksIEEE Transactions on Computational Social Systems10.1109/TCSS.2024.339978411:5(6966-6981)Online publication date: Oct-2024
https://doi.org/10.1109/TCSS.2024.3399784
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Index Terms

Event-based social networks: linking the online and offline social worlds
1. Information systems
  1. Information storage systems
    1. Storage architectures
      1. Storage network architectures

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cover image ACM Conferences

KDD '12: Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining

August 2012

1616 pages

ISBN:9781450314626

DOI:10.1145/2339530

General Chair:
Qiang Yang
Hong Kong University of Science and Technology
,
Program Chairs:
Deepak Agarwal
LinkedIn
,
Jian Pei
Simon Fraser University

Copyright © 2012 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 12 August 2012

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KDD '12

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KDD '12: The 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining

August 12 - 16, 2012

Beijing, China

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Overall Acceptance Rate 1,133 of 8,635 submissions, 13%

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Zhang SMeng XZhang Y(2024)Variational Type Graph Autoencoder for Denoising on Event RecommendationACM Transactions on Information Systems10.1145/370315643:1(1-27)Online publication date: 5-Nov-2024
https://dl.acm.org/doi/10.1145/3703156
Zhu ZYuan GZhou TCao J(2024)Community Detection for Heterogeneous Multiple Social NetworksIEEE Transactions on Computational Social Systems10.1109/TCSS.2024.339978411:5(6966-6981)Online publication date: Oct-2024
https://doi.org/10.1109/TCSS.2024.3399784
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Seedath AHosein NHosein P(2024)Predicting Event Participation for an Event-Based Social Network2024 IEEE International Conference on Technology Management, Operations and Decisions (ICTMOD)10.1109/ICTMOD63116.2024.10878202(1-6)Online publication date: 4-Nov-2024
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